Printer-friendly format

Four years ago, anonymous people in various populations of America, Nigeria, Tokyo and Beijing allowed for samples of their DNA to be obtained for an extensive genetic study. Researchers hoped to navigate and catalog the patterns of genetic variation that are common in the world's population.

The results have provided overwhelming evidence that variation in the human genome is organized into local neighborhoods, called haplotypes, which usually are inherited as intact blocks of information. This momentous achievement has already accelerated the hunt for genes involved in common diseases such as cancer, diabetes and heart disease.

A public-private effort through the National Institutes of Health, National Human Genome Research Institute (NHGRI), research organizations and biotechnology companies, this international consortium set and completed the three-year goal of creating a human haplotype map, known as the HapMap.

Now, the Phase I HapMap consists of more than 1 million markers of genetic variation, called single nucleotide polymorphisms (SNPs, pronounced "snips"). SNPs are alternative spellings, or misspellings, that generally happen in the order of the DNA base pairs, or letters, that make up a person's genome. It is estimated that there are approximately 10 million SNPs that occur commonly in the human genome.

This HapMap is a natural extension of the Human Genome Project that culminated in April 2003. While the Human Genome Project focused on what we have in common in the genome, the HapMap creates an atlas of genetic variations and how these differences play a role in human health. Any two individuals are 99.9 percent identical at the genetic level. This data makes possible the ability to study and ultimately understand the 0.1 percent difference because that small disparity can help explain why one person is more susceptible to a disease or responds differently to a drug or environmental factor than another.

"The HapMap really focuses on the variation between people … it's not the end of the story, but it's a huge step forward in trying to understand the variation, how it's inherited or particularly to give us tools to figure out how the variation really functions and how it [plays a role in] disease," explains Dr. Alan Guttmacher, deputy director of NHGRI. "That's very important because what we've done before the HapMap to find genes involved in diseases was a candidate gene approach. This whole genome approach allows us to go in without any preconceived ideas to find out what genes are involved."

According to the NHGRI, with these haplotypes defined, HapMap provides an efficient method for choosing "tag SNPs" that capture the genetic variation in each neighborhood with a minimum amount of work. Comparing patterns in affected and unaffected people helps to survey the variations and identify the genetic contributions to common diseases in a way that was never before possible.

In 2002, if scientists had wanted to embark on a study to detect a variant gene in the whole genome, using the standard 2,000 people who are genetically matched but distinguished by being affected or unaffected by a particular disease, the cost would have been $10 billion, says Guttmacher … a fee no one was going to pay. What the HapMap has been able to do is to identify the tag SNPs that uniquely define a haplotype. With an estimated 300,000-600,000 tag SNPs, far fewer than the 10 million common SNPs, HapMap is greatly reducing research time. This has also unimaginably reduced the costs down to $2 million to $3 million for the same kind of study, opening the door to tremendous research opportunities.

Genetic detectives around the world have promptly recognized the potential of the HapMap, accessing its publicly available "snip" or SNP datasets even before the first phase of the map was completed. Studies were published this year in which scientists used the HapMap data to uncover genes that substantially increase the risk of age-related macular degeneration, the leading cause of severe vision loss in the elderly. The study of this single spelling variant out of the 3 billion letter DNA human codebook shows the genes involved in the disease are coded for a protein involved in inflammation. This directs the way for development of better diagnostic tests and treatments for this incapacitating disease.

"When they were using [the HapMap] approach, they were able to show the genes involved were not the genes we necessarily expected to be involved," Guttmacher explains. "That's exactly the kind of thing we hoped would come out of the HapMap … being able to identify genes that play a role in common disease that we hadn't realized before and using that knowledge to treat the disease more effectively and particularly prevent people from developing the disease."

Nevertheless, it's imperative the research community not jump to conclusions too quickly when using the HapMap to facilitate its own whole-gene association studies. So far, studies are full of statistical pitfalls, leaving the possibility that genes found with this approach won't stand up to later analysis.

As with any research endeavor, scientists are urged to confirm any gene "discovery" by replicating the findings with independent studies using the same SNP markers in different groups of people with the same disease.

Phase II of the HapMap is expected to be completed this fall and will contain nearly three times more markers than the initial version. This will enable researchers to focus gene searches even more precisely on specific regions of the genome.



Two New Initiatives in

Whole Genome Association

The HapMap data has already spread quickly through the research world, and a new budget is being presented to Congress to fund two important studies using the whole-genome association approach. In February, the presidential budget presented to Congress included a $68 million Genes and Environment Initiative (GEI), a multi-institute research effort to understand both the genetic and environmental foundations of common illnesses.

GEI will have two main components: genotyping for several common diseases (which will be chosen by a peer review) and technology development to devise innovative ways of monitoring personal environmental exposures that interact with genetic variations and result in human disease.

"This initiative would not have been possible a year or two ago," said director of the NIH Dr. Elias A. Zerhouni at the February initiative announcement. "This is a tangible result of the nation's increased investment in medical research over the past 10 years. We are now poised to combine what we have learned from years of population studies, with newly available technologies, developed with NIH support. We stand on the threshold of creating a future that will revolutionize the practice of medicine by allowing us to predict disease, develop more precise therapies and ultimately, preempt the development of disease in the first place."

In addition to the GEI initiative, a public-private partnership between the NIH, the Foundation for the NIH (a nonprofit foundation established by Congress to support the mission of the NIH), Pfizer and Affymetrix is being created to further accelerate this vital research in whole genome association studies.

This new partnership, called the Genetic Association Information Network (GAIN), is being launched with donations from Pfizer to set up laboratory studies to determine the genetic contributions of five diseases. Affymetrix, a biotech company that develops the types of tools used in these genetic studies, will contribute enough laboratory resources to study two additional common diseases.

As explained by the NIH, the genetic analysis of both GEI and GAIN will focus on those DNA letter misspellings, or SNPs, in the 3 billion genome base pairs. SNPs are like single-letter misspellings of a word which typically are biologically meaningless, but a small fraction of these misspellings alter the function of a gene, often only slightly. The combination of many slightly altered genes may substantially increase the risk of a specific disease.

Differences in our genetic makeup influence our risk of developing illnesses, but genes alone do not illuminate the whole picture.

"We need to realize that just because we understand the genetic contribution to disease far better than we ever have before doesn't suddenly make genes more important to health and disease as they were before," explains Guttmacher. "All of health and disease is a combination of genetic and nongenetic factors. It's the interplay of those that we need to really understand health and disease."

Recent increases in diseases like diabetes, childhood asthma, obesity or autism cannot be due to major shifts in the human gene pool. Scientists believe they must be due to changes in the environment, including diet and physical activity, which may create an environment for disease in a genetically predisposed person. That is why GEI will also invest in innovative, new technologies to measure environmental toxins, dietary intake and physical activity, as well as to determine an individual's biological response to those influences using new tools of genomics, proteomics and metabolomics. Such emerging technology includes small wearable sensors that can measure environmental agents that have contact with the body and individual measures of activity.

Through these genetic and environmental studies, researchers hope to ultimately figure out why only certain people develop a disease and why prognoses are so different from one person to the next.



The Cancer Genome Atlas

Imagine a day when physicians can tell patients that based on their genetic makeup, specific environmental triggers could create an atmosphere for a malignancy. Imagine being able to tell a patient that taking a particular medication could block certain receptors in her body from mingling with those outside triggers and thus prevent a disease from forming. Researchers with the National Cancer Institute (NCI) and the NHGRI are hoping for just that scenario in the not-to-distant future.

In December, these two organizations launched a comprehensive effort, each committing $50 million over three years into a pilot project to expand the understanding of the molecular basis of cancer through the application of the whole-genome analysis technologies, particularly large-scale genome sequencing. As explained by the NIH, this overall effort, called The Cancer Genome Atlas (TCGA), has begun with a pilot project to determine the feasibility of a full-scale effort to systematically explore the universe of genomic changes involved in all types of human cancer.

Today cancer is understood to include more than 200 different diseases. In all forms of cancer, genomic changes cause disruptions within cellular pathways that result in uncontrolled cell growth. The Human Genome Project helped advance genetic sequencing technologies, and the HapMap further advanced genotyping to allow for quicker and more comprehensive research. Both of these projects created the necessary tools for producing new insights into how and why genetic changes cause cancer. Genetic mutations linked to breast cancer, colon cancer, melanoma and other cancers have already led to diagnostic tests that can point to the most effective interventions. Recent discoveries in cancer genomics have helped to identify several treatments that work by targeting cancer cells with a specific change, such as Gleevec®, a drug for chronic myeloid leukemia and gastrointestinal tumors, and Herceptin®, a drug for one form of breast cancer.

By delving deeper into the genetic origins leading to the complex cancer diseases, TCGA will be able to create novel discoveries and tools for a new generation of cancer therapies, diagnostics and preventive strategies.

As in the Human Genome Project and HapMap, TCGA data will be made available to the worldwide research community. This data will provide researchers and clinicians with an early glimpse of what is hoped to evolve into an unprecedented, comprehensive "atlas" of information describing the genomes of all cancers. If successful, the information will enable researchers to then use that data to develop new diagnostics and therapies for different cancers.

Each component of the TCGA pilot project will have clear milestones and goals. Only if the pilot achieves its goals will the full-scale project to develop a complete atlas of the cancer genome move forward.

"Our problem today in medicine is we still, by and large, treat people as categories of humanity," says Guttmacher. "The problem is, nobody who walks into a doctor's office is a category of humanity. Every patient is an individual. The more we can treat the patient as the biological and psychological individual that they are, the better their healthcare will be and the more ownership they will feel of their own healthcare. This whole pathway is towards is more personalized, predictive, preventive medicine."

What was once science fiction is steadily becoming reality. While there are no doubt social and ethical implications, as science works to understand our individual biology, we could see the day when medical prevention of deadly diseases is a reality.

Tags:

None